US20080063998 describes a technique wherein one fluorescence image and one reflectance image are combined to form an image in which the contrast between a cariogenic region and a sound tooth structure is heightened in the 2D image.
US2008094631 describes a system with intraoral camera and measuring device. The measuring device is capable of collecting color, translucency, fluorescence, gloss, surface texture and/or other data for a particular tooth from the measuring device which then may be combined with images captured by intraoral camera.
Optical 3D scanners for recording the topographic characteristics of surfaces within the intraoral cavity, particularly of the dentition, are known in the prior art (e.g., WO2010145669). Examples of commercially available 3D intraoral scanners are 3Shape TRIOS, Cadent iTero, Sirona Cerec, and 3M Lava C.O.S.
The size of any probe element in intraoral scanners is limited because it has to fit into the human mouth. Accordingly, the field of view of such scanners is smaller than the object of interest in many applications, which can be multiple neighboring teeth or an entire dental arch. Hence, intraoral 3D scanners rely on “stitching” several sub-scans, each representative of a field of view, but obtained in multiple positions, e.g., by moving the 3D scanner along the dental arch. The 3D scanner records a series of sub-scans that are to be stitched to yield an overall digital 3D representation of the surface topography for the scanned part of the intraoral cavity. A sub-scan represents a depth map for a given relative position and orientation of the 3D scanner and the patient's intraoral cavity. To obtain multiple sub-scans, the 3D scanner is moved along the intraoral cavity or some region thereof and potentially also angled differently. The 3D scanner is to be moved and angled such that at least some sets of sub-scans overlap at least partially, in order to enable stitching. The result of stitching is a digital 3D representation of a surface larger than that which can be captured by a single sub-scan, i.e. which is larger than the field of view of the 3D scanner. Stitching, also known as registration, works by identifying overlapping regions of 3D surface in various sub-scans and transforming sub-scans to a common coordinate system such that the overlapping regions match, finally yielding the overall scan. The Iterative Closest Point (ICP) algorithm is widely used for this purpose.